Genomics-EHR Integration via FHIR Normalization
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Solution Overview
Problem
Conventional medical informatics systems face challenges in integrating and displaying genomic data due to its voluminous and complex nature, differing standards between bioinformatics and clinical informatics, and limited understanding of bioinformatics data specifications, which hinders effective searching and aggregation, making it difficult to provide personalized medicine and early disease detection.
Innovation Solution
A user interface and computer system that generates a structured data set from clinical and genomic data, creating a virtual representation of a patient's medical record with graphical components that map to anatomical features and gene variants, allowing for interaction and display of detailed information, including genomic and clinical data, using FHIR genomics operations for normalization and interoperability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If genomic data is integrated into conventional EHR systems, then personalized medicine and early disease detection are enabled, but data complexity and normalization challenges increase
Solution Approach 1:
The patent introduces FHIR Genomics as an intermediary layer between raw genomic data and clinical EHR systems. This mediator handles the complex normalization and standardization of genomic variants, converting diverse sequencing data formats into standardized representations that can be integrated into conventional EHR workflows without requiring clinicians to understand underlying bioinformatics complexity.
Solution Approach 2:
The system segments genomic data processing into distinct layers: raw sequencing data, normalized variant representations, and clinical interpretations. This segmentation allows each layer to be handled independently with appropriate tools and standards, reducing the overall complexity of integration while enabling personalized medicine capabilities.
2Measurement precision
If comprehensive genomic data is stored and accessed, then disease risk identification is improved, but data storage and processing resources increase
Solution Approach 1:
The patent extracts and stores only the clinically relevant genomic variants rather than preserving all raw sequencing data. By identifying and storing only pathogenic and likely pathogenic variants in standardized formats, the system maintains high disease risk detection accuracy while significantly reducing storage requirements compared to keeping complete genomic datasets.
3Adaptability or versatility
If genomic data standards are harmonized with clinical informatics, then data interoperability is improved, but implementation effort and cost increase
Solution Approach 1:
The patent implements FHIR Genomics as a universal standard that serves multiple functions: it provides standardized variant representations, enables interoperability between different sequencing platforms and EHR systems, and supports both research and clinical applications. This multi-functionality justifies the implementation investment by delivering broad interoperability benefits across diverse use cases.
Data Source
AI summary
This invention relates to the field of medical informatics, and more particularly to a system and methods for generating and displaying a user interface of a patient medical record such that a user can annotate, augment, and overall interact with clinically more accurate and detailed medical information. In addition, the system may be configured to collect, display, and model an individual's genomic makeup, physiological characteristics, healthcare history, and lifestyle to enable personalized medicine, better understand the transition from health to disease, and identify additional risk factors for disease. Advantageously, the system is configured to collect, display, and model an individual's genomic makeup, health status, health history, and social determinants of health to enable personalized medicine, better understand the transition from health to disease, and identify additional risk factors for disease.